loop through pandas dataframe code example

Example 1: pandas loop through rows

for index, row in df.iterrows():
    print(row['c1'], row['c2'])

Output: 
   10 100
   11 110
   12 120

Example 2: iterate over rows dataframe

df = pd.DataFrame([{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}])
for index, row in df.iterrows():
    print(row['c1'], row['c2'])

Example 3: creating data frame in python with for loop

df = pd.DataFrame(columns=["A", "B"])

for i in range(2):
    this_column = df.columns[i]
    df[this_column] = [i, i+1]

print(df)

#OUTPUT
#  A B
#0 0 1
#1 1 2

Example 4: python - iterate with the data frame

# Option 1
for row in df.iterrows():
    print row.loc[0,'A']
    print row.A
    print row.index()

# Option 2
for i in range(len(df)) : 
  print(df.iloc[i, 0], df.iloc[i, 2])

Example 5: dataframe for loop

import pandas as pd 
  
# Define a dictionary containing students data 
data = {'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka'], 
                'Age': [21, 19, 20, 18], 
                'Stream': ['Math', 'Commerce', 'Arts', 'Biology'], 
                'Percentage': [88, 92, 95, 70]} 
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, columns = ['Name', 'Age', 'Stream', 'Percentage']) 
  
print("Given Dataframe :\n", df) 
  
print("\nIterating over rows using iterrows() method :\n") 
  
# iterate through each row and select  
# 'Name' and 'Age' column respectively. 
for index, row in df.iterrows(): 
    print (row["Name"], row["Age"])

Example 6: python loop through column in dataframe

# Iterate over two given columns only from the dataframe
for column in empDfObj[['Name', 'City']]:
   # Select column contents by column name using [] operator
   columnSeriesObj = empDfObj[column]
   print('Colunm Name : ', column)
   print('Column Contents : ', columnSeriesObj.values)

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